System and method for monitoring disposal of wastewater in one or more disposal wells

ABSTRACT

A system and method for monitoring disposal of wastewater in a disposal well includes: an event monitor sensor configured to identify a wastewater disposal event; and a second sensor configured to collect data about one or more characteristics of the wastewater during the wastewater disposal event. The data from the second sensor at the disposal well is analyzed to determine a classification of the wastewater, which is then reported to an operator or another interested party.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims priority to U.S. patent application Ser.No. 62/477,088 filed on Mar. 27, 2017, which is incorporated herein byreference.

BACKGROUND OF THE INVENTION

In oil-producing and gas-producing regions, hydrocarbon exploration andproduction companies require water when drilling wells using hydraulicfracturing. Furthermore, producers need a location to dispose of boththe used fracturing fluid (flow-back water) and the water that isproduced naturally alongside the hydrocarbons (produced water).

In many cases, depending on state, regional, or federal regulations, theflow-back and produced water is deposited into a dedicated disposalwell. Such a disposal well may also be referred to as a saltwaterdisposal well (SWD) or a wastewater disposal well. Disposal wells areoften operated in remote areas, often unmanned by any staff ormanagement to oversee disposal events. Subsequently, operators oftenlack insight into key details of the daily operations of a disposalwell. These details include, among others, site security, recordkeeping,billing, and scheduling of preventative maintenance.

In many instances, wastewater disposal events are self-reported by thedriver of a disposal truck. The operator has little recourse to verifythat information regarding a disposed quantity of water, such as thetype and volume of water, is accurate or even correct. An operator maycharge vastly different rates for disposal of different fluid types andis incentivized to ensure there is as little error as possible.Furthermore, paper records are often the only records of disposalevents, which may be difficult to audit to verify that events werereported accurately.

Additionally, operators may be actively engaged in buying or sellingservices in a water disposal marketplace where operational data isvaluable. For instance, an operator may advertise its current prices forits disposal services in an effort to attract truck drivers who arehauling waste to use those services. Factors that influence the pricemight include, but are not limited to, disposal capacity, trafficvolumes, well pressures, tank levels, or volumes of different types ofwastewater over time. If the operator can automatically measure andcommunicate these types of data to the wider market, it can realizecertain operational efficiencies.

SUMMARY OF THE INVENTION

The present invention is a system and method for monitoring disposal ofwastewater in one or more disposal wells.

In the system and method of the present invention, disposal wells areoutfitted with sensors to determine information related to wastewaterthat is disposed in the well, and that information is then delivered tothe operator of the disposal well. Specifically, in the system method ofthe present invention, disposal of wastewater in disposal wells ismonitored by analyzing wastewater that is disposed in a monitored well.Furthermore, a rules-based classification system is employed to automatedetection and classification of future disposal events. Furthermore, thesystem and method of the present invention allows the wastewaterdisposal information to be leveraged to predict and characterize energycommodity extraction in a region.

In an exemplary system made in accordance with the present invention, awell facility, which may include one or more disposal wells, includes anevent monitor sensor associated with each of the one or more wells. Theevent monitor sensor comprises one or more sensors to identify thepresence of a volume of wastewater to be disposed and/or of a wastewaterdisposal event. In some embodiments, the event monitor sensor is acamera or similar imaging device that collects images to determine thestart and/or completion of a wastewater disposal event. In someembodiments, rather than use a camera or similar imaging device, theevent monitor sensor is a laser beam and photo-eye combination that istripped or broken when a truck passes through the path of the beam, thusidentifying the start and/or completion of a wastewater disposal event.In some embodiments, the event monitor sensor is a coil of wire embeddedin the road, a pneumatic tube, or a vibration sensor that can detectwhen a truck passes over it, each of which can identify the start and/orcompletion of a wastewater disposal event. Finally, in some embodiments,a pump associated with a well is monitored by the event monitor sensor;for example, the event monitor sensor may be a current sensor that isused to monitor the power consumption of one or more pumps that areassociated with the well.

Irrespective of the type of sensor employed, the event monitor sensorcollects data, and the collected data is then transmitted to the centralprocessing facility, where the collected data is stored in a databasefor subsequent use or analysis.

In an exemplary system made in accordance with the present invention,the well facility further includes a second sensor (or sensors)associated with the well. The second sensor measures one or morecharacteristics of the wastewater that is being disposed in the well.For example, the second sensor may be one or more of: a total suspendedsolids (TSS) sensor; a sensor; and a conductivity sensor. Irrespectiveof the type of sensor employed, the collected data is then alsotransmitted to the central processing facility and stored in a database.

The collected data is then analyzed using a water analysis module, whichmakes use of a digital computer program, i.e., computer-readableinstructions stored and executed by a computer, to carry out theanalysis. In one exemplary implementation, the analysis carried out bythe water analysis module commences with the collection and cleaning ofthe data, which may be accomplished, for example, by applying transformsto create uniform date/time formats and/or removing duplicate rows.Statistics are then computed for the disposed wastewater during thewastewater disposal event. Finally, the collected (and cleaned) data isthen analyzed to determine a classification for the wastewater, forexample, by applying a water classification model.

The water classification model is a function hat maps an input variable(i.e., collected data from the second sensor) to one or more discreteclasses (i.e., water classifications). In this particular case, theobjective is to distinguish between four different classes ofwastewater: (i) produced water; (ii) flow-back water; (iii) pit water:and (iv) basic sediment and waste (BSW). Common models that may be used,for example, are decision trees, nearest neighbor classifiers, logisticregression models, and support vector machines. In each case, the waterclassification model is built and established by using a training set ofwater information from an external source (or “truth data”) and thencorrelating that water information to collected (and cleaned) data fromthe second sensor. No matter which type of model is used, the objectiveis to create a model that accurately predicts the values of the unknownor future values. For example, since collected data from the secondsensor may be from total suspended solids (TSS) sensor, a pH sensor,conductivity sensor (or other sensor), data about total suspendedsolids, pH, and/or conductivity may all be inputs into a waterclassification model that delivers as its output a classification ofwastewater: (i) produced water; (ii) flow-back water; (iii) pit water;or (iv) basic sediment and waste (BSW). Once built and established, thewater classification model is applied to subsequently collected (andcleaned) data to determine a classification for the wastewater during aparticular wastewater disposal event.

Finally, the classification, along with statistics for the disposedwastewater during the wastewater disposal event, is communicated to anoperator or other interested parties. It is contemplated and preferredthat such communication to the operator or other interested partiescould be achieved through electronic mail delivery and/or through exportof the data to an access-controlled Internet web site, which theoperator or other interested parties can access through a commonInternet browser program.

In addition to being utilized by an operator of a well facility, thesystem and method of the present invention may be further leveraged topredict and analyze energy commodity and/or water consumption in aregion.

DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic representation of an exemplary system made inaccordance with the present invention;

FIG. 2 is a flow chart illustrating the steps of an analysis carried outby the water analysis module in an exemplary implementation of thepresent invention; and

FIG. 3 is a plot of a logistics function.

DETAILED DESCRIPTION OF THE INVENTION

The present invention is a system and method for monitoring disposal ofwastewater in one or more disposal wells.

In the system and method of the present invention, disposal wells areoutfitted with sensors to determine information related to wastewaterthat is disposed in the well, and that information is then delivered tothe operator of the disposal well. Specifically, in the system andmethod of the present invention, disposal of wastewater in disposalwells is monitored by analyzing wastewater that is disposed in amonitored well. Furthermore, a rifles-based classification system isemployed to automate detection and classification of future disposalevents. Furthermore, the system and method of the present inventionallows the wastewater disposal information to be leveraged to predictand characterize energy commodity extraction in a region.

FIG. 1 is a schematic representation of an exemplary system made inaccordance with the present invention. A well facility 10 is illustratedas including a single well 15 for simplicity, but a well facility 10 mayinclude multiple wells 15 within the facility. The well facility 10further includes an event monitor sensor 20 associated with the well 15.The event monitor sensor 20 comprises one or more sensors to identifythe presence of a volume of wastewater to be disposed and/or of awastewater disposal event.

in some embodiments, the event monitor sensor 20 is a camera or similarimaging device that collects images to determine the start and/orcompletion of a wastewater disposal event. For example, the wastewaterdisposal event may be defined as a disposal truck entering andsubsequently exiting the well facility 10. Truck arrival and departuretimes may be determined by analyzing images of the well facility 10 thatare captured by the camera or similar imaging device, which, of course,would be mounted or otherwise positioned so that it has a sufficientview of the well facility 10, particularly the bays in which trucksunload wastewater. For example, one camera that may be used for suchimage capture is the Axis Q1775 Network Camera manufactured by AxisCommunications AB of Lund, Sweden.

The event monitor sensor 20 may collect images at a set time interval,for instance, once every three minutes. Furthermore, as shown in FIG. 1,the collected images are then preferably transmitted to a centralprocessing facility 60, where the collected images are stored in adatabase 22 for subsequent use or analysis.

Event information can then be extracted from the collected images usingone of several techniques. For example, in some embodiments, a humancould curate collected images to identify the arrival and departuretimes of trucks. Alternatively, the collected images could be analyzedvia crowdsourcing (using platforms such as Amazon Mechanical Turk orCrowdFlower) to allow for faster human processing of the images.

In other embodiments, the collected images are analyzed utilizing animage analysis module 24 at the central processing facility 60, whichmakes use of a digital computer program, i.e., computer-readableinstructions stored and executed by a computer, to carry out theanalysis. For example, the collected images may be organized inchronological order, and the image analysis module 24 could then be usedto detect changes in the images, such as the arrival and/or departure ofa truck. The image analysis module 24 may then also detect the startand/or completion of a wastewater disposal event by identifying thefirst image (and time of the image) that a truck is visible in an image,and subsequently identify the last image (and time of the image) thatthe same truck is visible. From such an image analysis, a wastewaterdisposal event is identified.

As a further refinement, in some embodiments, collected images may befurther utilized to identify and track additional information related tothe customers of the well facility 10. For instance, particular trucks,truck drivers, and trucking companies may be identified based onanalysis of the collected images from the event monitor sensor 20 orother imaging device. For example, in some embodiments, identifyingmarks from each truck may be captured. This can be done by employingoptical character recognition (OCR) technology to read, for example, thelicense plate, the waste hauling permit (WHP) number, the company name,or other text from the truck itself. One exemplary imaging system is theAutoVu™ automatic license plate recognition (ALPR) system manufacturedby Genetec, Inc. of Montreal, Quebec, Canada. In other embodiments,visual information may be collected by cameras positioned outside of theoperator's property to capture details on vehicle identifying marks orvehicular traffic in general. These cameras are positioned so that therelevant information is captured. They may be installed, for instance,above or near the roadway outside the facility. Additionally, thecameras may be positioned remotely, for instance, mounted to an aerialvehicle or satellite. In any event, by independently identifying andmatching a wastewater disposal event to a certain truck, truck driver,or trucking company, record-keeping and billing may be further automatedto ensure the operator of the well facility 10 is properly compensatedfor all wastewater disposal events.

In some embodiments, rather than use a camera or similar imaging device,the event monitor sensor 20 is a laser beam and photo-eye combinationthat is tripped or broken when a truck passes through the path of thebeam, thus identifying the start and/or completion of a wastewaterdisposal event.

In some embodiments, the event monitor sensor 20 is a coil of wireembedded in the road, a pneumatic tube, or a vibration sensor that candetect when a truck passes over it, each of which can identify the startand/or completion of a wastewater disposal event.

In some embodiments, a pump associated with a well 15 is monitored bythe event monitor sensor 20. For example, the event monitor sensor 20may be a current sensor that is used to monitor the power consumption ofone or more pumps that are associated with the well 15. Specifically,the event monitor sensor 20 (or current sensor) may be used to determinewhen a pump turns on or off, or how long a pump associated with the well15 is in operation. Such monitoring of current flowing to a pump isdescribed in U.S. Patent Publication No. 2016/0019482, which is entitled“Method and System for Monitoring a Production Facility for a RenewableFuel” and is incorporated herein by reference. As described therein,current sensors are placed on power cables associated with one or morepumps; such placement is preferably non-invasive (e.g., around the powercables) and does not interrupt operation. For example, one preferredsensor for use in the system and method of the present invention is aPAN-series current sensor manufactured by Panoramic Power Ltd of KfarSaba, Israel, one of which would be placed on a power cable for each ofthe pumps of the well 15

In some embodiments, such a current sensor may be remotely positioned,for instance, near electric power transmission lines that are connectedto and supplying power to the facility. In this instance, the currentsensors do not come in contact with the wires through which they aremeasuring the current. Instead, the sensors are arranged to remotelymeasure the magnetic and electric fields produced by the conductors ofthe electric power transmission lines and calculate the power movingthrough the conductors, as described, for example, in U.S. Pat. No.6,771,058 entitled “Apparatus and Method for the Measurement andMonitoring of Electrical Power Generation and Transmission” and U.S.Pat. No. 6,714,000 entitled “Apparatus and Method for Monitoring Powerand Current Flow,” each of which is incorporated herein by reference.

Again, the event monitor sensor 20 may collect data at a set timeinterval, for instance, once every three minutes, and the collected datais then preferably transmitted to the central processing facility 60,where the collected data is stored in a database 22 for subsequent useor analysis,

With respect to collected current data, to convert such current data tooperational status information, the current data is analyzed using acurrent analysis module 26, which makes use of a digital computerprogram, i.e., computer-readable instructions stored and executed by acomputer, to carry out the analysis. In the current analysis module 26,the analog data is digitized based on a given threshold. If the measuredcurrent is above the threshold, the pump is considered to be “ON,”whereas, if the measured current is below the threshold, the pump isconsidered to be “OFF.” The time at which the pump transitions from onestate to another can then be extracted from the data. From this datastream, information about when the pump turned on, when it turned off,and how long it was in operation for a given period can be generated.

In order to determine how much fluid has flown through the pump duringoperation (i.e., during a wastewater disposal event), it is necessary tocreate a model relating pump current to the fluid flow rate, for a givenset of fluid properties. Then, this current-to-flow-rate mapping can beapplied to future events. Such creation of transforms which takescollected data and transforms the collected data into operationalstatuses is also described in U.S. Patent Publication No. 2016/0019482,which is entitled “Method and System for Monitoring a ProductionFacility for a Renewable Fuel” and is incorporated herein by reference.

Additionally, pumping events may be determined by making use ofoperator-supplied data streams, such as those created by a supervisorycontrol and data acquisition (SCADA) system. As part of this SCADAsystem, a tablet, laptop, personal computer, or other input device maybe used by the truck drivers or pump operators to input characteristicsabout a load of wastewater. For instance, the operator may input thearrival time, departure time, volume of wastewater disposed of,wastewater classification, license plate number, waste hauler permitnumber, or department of transportation permit number of a truck. Thisinput method is tied to the operator's backend financial accountingsystem, where the data can be stored in a database and retrieved asneeded.

Referring again to FIG. 1, the well facility 10 further includes asecond sensor 30 (or sensors)associated with the well 15. The secondsensor 30 measures one or more characteristics of the wastewater that isbeing disposed in the well 15. For example, in some embodiments, thesecond sensor 30 is a total suspended solids (TSS) sensor, such as theModel 950 Suspended Solids Monitor manufactured by ConfabInstrumentation of Jackson, Calif. As wastewater is disposed in the well15, the TSS sensor monitors total suspended solids in the wastewater.For another example, in other embodiments, the second sensor 30 is a pHsensor, such as the Model DPD1P1 Online Process pH Sensor manufacturedby Hach Lange GmbH of Dusseldorf, Germany. For yet another example, inother embodiments, the second sensor 30 is a conductivity sensor, suchas the 3700 Series Analog Inductive Conductivity Sensor manufactured byHach Lange GmbH of Dusseldorf, Germany.

Referring again to FIG. 1, irrespective of the type of sensor employed,the collected data is then preferably transmitted to the centralprocessing facility 60 and stored in a database 32. The collected datais then analyzed using a water analysis module 34, which makes use of adigital computer program, i.e., computer-readable instructions storedand executed by a computer, to carry out the analysis. For example, aremote backhaul device, such as the Wavelet device manufactured byAyyeka Technologies of Jerusalem, Israel, may be utilized to sample andcollect data from the second sensor 30 and then communicate thecollected data to the water analysis module 34 at the central processingfacility 60 for analysis.

In this exemplary implementation, and referring now to FIG. 2, theanalysis carried out by the water analysis module 34 commences with thecollection and cleaning of the data, as indicated by block 200. In thisregard, data may be collected from the second sensor 30 (or sensors) atthe well 15 on a substantially continuous basis, for example, at somefixed frequency, such as every one minute. Alternatively, datacollection may be initiated when there is an indication of an occurrenceof a wastewater disposal event. The indication of the occurrence of thewastewater disposal event may he based on the data from the eventmonitor sensor 20. For example, as described above, the event monitorsensor 20 may identify that a wastewater disposal event has begun byimage analysis and/or pump current monitoring, at which time the secondsensor 30 starts collecting data. Similarly, the event monitor sensor 20may provide a signal to indicate that a wastewater disposal event hasconcluded, at which time the second sensor 30 stops collecting data.

Referring still to FIG. 2, with respect to the cleaning of the data,this may be accomplished by, for example, applying transforms to createuniform date/time formats and/or removing duplicate rows.

Referring still to FIG. 2, statistics are then computed for the disposedwastewater during the wastewater disposal event, as indicated by block210. For example, a wastewater disposal event may be defined as onetruck entering the well facility 10, unloading its wastewater, and thenexiting the well facility 10. Relevant data would be collected from thesecond sensor 30 (or sensors) only when the pump utilized by that truckto unload its wastewater is running. In other words, with respect to theexemplary sensor types disclosed above, the total suspended solids, pH,and/or conductivity measurements are all irrelevant when there is nowastewater being disposed. Thus, the analysis focuses on the time periodof the wastewater disposal event. For example, as discussed above, thetime at which a pump turned on (pump start time) and the time at which apump turned off (pump stop time) can both be determined by the eventmonitor sensor 20. Therefore, the water analysis module 34 only needs toanalyze data from the second sensor 30 (or sensors) during thewastewater disposal event. Statistics such as mean, standard deviation,maximum, and minimum can then be found easily for each of the waterquality metrics within the time window defined by the wastewaterdisposal event.

Referring still to FIG. 2, the collected (and cleaned) data is thenanalyzed to determine a classification for the wastewater. Suchclassification may be determined, for example, by applying a waterclassification model, as indicated by block 220 in FIG. 2.

Referring again to FIG. 1, to establish a water classification model, awater classification module 40 receives water information from anexternal source 50. This water information is “truth data” that isaccurate information about the wastewater that was pumped into the well15 during a given wastewater disposal event; for example, for initialtraining establishment of the water classification model, such waterinformation may come from or be derived from operator records. In someimplementations, water information is split into a training set and atest set instance, in some implementations, approximately 80% of thewater information data is classified as the training set, while 20% ofthe water information is classified as the test set, although this canvary on a case-by-case basis. This allows for the water classificationmodel to be built using the training set, and then subsequently appliedto the test set to assess its accuracy, as further described below.

In its simplest form, the water classification model is a function thatmaps an input variable (i.e., collected data from the second sensor 30)to one or more discrete classes (i.e., water classifications). In thisparticular case, the objective is to distinguish between four differentclasses of wastewater: (i) produced water; (ii) flow-back water; (iii)pit water; and (iv) basic sediment and waste (BSW). Common models thatmay be used, for example, are decision trees, nearest neighborclassifiers, logistic regression models, and support vector machines. Ineach case, the water classification model is built and established byusing the training set of water information from an external source 50(or “truth data”) and then correlating that water information tocollected (and cleaned) data from the second sensor 30. No matter whichtype of model is used, the objective is to create a model thataccurately predicts the values of the unknown or future values. Forexample, since collected data from the second sensor 30 may be from atotal suspended solids (TSS) sensor, a pH sensor, conductivity sensor(or other sensor), data about total suspended solids, pH, and/orconductivity may all be inputs into a water classification model thatdelivers as its output a classification of wastewater: (i) producedwater; (ii) flow-back water; (iii) pit water; or (iv) basic sediment andwaste (BSW).

For example, one specific method for classifying wastewater is based onthe use of a logistic regression model. A logistic regression is a typeof model that tries to predict the value of a discrete binary variable,Y, given one or more independent variables, X. It can answer questionssuch as: “Did a student pass or fail this test?” or “Was this subjecthealthy or sick?” Moreover, a logistic regression model can provide aprobability that a certain example fits into one class or the other. Forinstance, the logistic regression model allows for statements such as“there is a 51% chance that it will rain today,” or “there is a 99%chance that it will snow tomorrow,” rather than simply stating that “itwill rain” or “it will snow.”

We can describe this model in a more formal way. The outcome, ordependent variable, is y. We know y can take only one of two values. Inthe case of the student passing a test, the value is either “pass” or“fail.” So, we can denote y taking on only these two values by:

y∈{0, 1}  (1)

Now, we want some function that can maximize the likelihood orprobability of y=1 when y really is 1, and y=0 when the opposite istrue. One function that achieves this is the logistic function:

$\begin{matrix}{{h_{\theta}(x)} = {{g\left( {\theta^{T}x} \right)} = \frac{1}{1 + e^{{- \theta^{T}}x}}}} & (2)\end{matrix}$

where θ represents a vector of weight parameters that are applied to x.More simply, with z=θ^(T)x, the equation can be rewritten as:

$\begin{matrix}{{g(z)} = \frac{1}{1 + e^{- z}}} & (3)\end{matrix}$

As shown in FIG. 3, when plotted, equation (3) results in an S-shapedcurve, in which g(z) tends toward 1 as z→∞ and tends toward 0 as z→−∞.

Therefore, the objective is to adjust the parameter θ so that when y=1,z=θ^(T)x is high, and when y=0, z=θ^(T)x is low:

P(y=1|x; θ)=h _(g)(x)   (4)

P(y=0|x; θ)=1−h _(g)(x)   (5)

Or, more concisely:

P(y|x; θ)=(h _(g)(x))^(y)(1−h _(g)(x))^(1−y)   (6)

Furthermore, the logistic regression model can be expanded to provideprobabilities in the case of more than two classes. In this particularcase, y is not binary and can assume more than two states. The logisticregression model is simply run for each possible state or class.

Again, in this particular case, the objective is to distinguish betweenfour different classes of wastewater: (i) produced water; (ii) flow-backwater; (iii) pit water; and (iv) basic sediment and waste (BSW). Thelogistic regression model is thus applied to predict whether a sample isproduced water, or not; whether it is flow-back water, or not; and soon. The results are then aggregated.

For example, the output from the application of one model on a smalldata set is presented in Table A below:

TABLE A Sam- True Predicted ple Fluid Predicted Predicted Pit PredictedCor- No. Type BSW Flowback Water Saltwater rect? 1 Pit Water 29% 0% 12%60% No 2 BSW 6% 0% 43% 51% No 3 Pit Water 0% 0% 98% 2% Yes 4 Pit Water0% 0% 98% 2% Yes 5 BSW 75% 0% 0% 25% Yes 6 Flowback 0% 100% 0% 0% Yes 7BSW 56% 0% 9% 36% Yes 8 BSW 62% 0% 31% 7% Yes 9 Pit Water 0% 0% 98% 2%Yes 10 Pit Water 30% 0% 63% 7% Yes 11 Flowback 0% 50% 50% 0% No 12 PitWater 0% 50% 50% 0% No 13 Saltwater 39% 0% 21% 40% Yes 14 Saltwater 13%0% 0% 87% Yes 15 Saltwater 6% 0% 0% 94% Yes 16 Saltwater 43% 0% 3% 54%Yes 17 Saltwater 21% 0% 14% 64% Yes 18 Saltwater 19% 0% 10% 70% Yes

Each row in Table A denotes one sample of wastewater. The column labeled“True Fluid Type” is the actual classification of that sample as givenby the operator. Each of the next four columns is a probability that thesample is in the identified one of the four classes. For example, SampleNo. 3 was pit water. Based on the pH, conductivity, and total suspendedsolids content of that sample, the model predicted that it had a 98%chance of being pit water, Thus, if a future sample had the sameproperties as Sample No. 3, the model would predict that the sample waspit water with 98% certainty

Again, the water classification model is built and established by usingthe water information from an external source (or “truth data”) and thencorrelating that water information to the collected (and cleaned) datafrom the second sensor 30. Once initially established, the model may beapplied once to the test set of water information in order to assess itsaccuracy. The water classification model is then stored in a memorycomponent that is part of or associated with the water classificationmodule 40.

Referring again to FIG. 2, as mentioned above, once built andestablished, the water classification model is applied to subsequentlycollected (and cleaned) data to determine a classification for thewastewater, as indicated by block 220.

Finally, the classification, along with statistics for the disposedwastewater during the wastewater disposal event, is communicated to anoperator or other interested parties, as indicated by block 230. It iscontemplated and preferred that such communication to the operator orother interested parties could be achieved through electronic maildelivery and/or through export of the data to an access-controlledInternet web site, which the operator or other interested parties canaccess through a common Internet browser program. For example, anoperator of the well facility 10 may be provided with a wastewaterclassification for a volume of wastewater. The operator may then verifywith a driver and/or customer who dumped the wastewater determine thatall records are accurate, that the customer was charged for the correcttype of wastewater disposal, and/or to otherwise ensure that thecustomer is representing the contents of the wastewater truthfully. Theinformation may also be delivered to a back-end accounting system thatallows the operator to, for instance, automatically send invoices, payexpenses, and comply with state, regional, and/or federal recordkeepingrequirements.

In addition to being used internally by the operator of a disposal well,information derived from the system may be automatically communicated tointerested water marketplace participants. For instance, the disposalwell operator may choose to communicate information about current wellstatus, current prices for various types of wastewater, current pumputilization rates, current disposal capacity, current trafficvolumes,current well pressures, current tank levels, and the like.

In addition to being utilized by an operator of a well facility 10, thesystem and method of the present invention may be further leveraged topredict and analyze energy commodity and/or water consumption in aregion. For example, the classification and other statistics for thedisposed wastewater during the wastewater disposal event may be providedto an aggregate system that collects wastewater classifications frommultiple wells and/or from multiple facilities. By identifying theamounts and types of wastewater that is being disposed of in a region,the aggregate system may infer and/or predict water needs for theregion. For another example, the aggregate system may be able to inferhydrocarbon extraction site characterizations, such as age of wells ormines, by possessing knowledge of the composition of wastewater in aregion. For yet another example, the aggregate system may inferinformation related to volume of hydrocarbon extraction in a regionbased on the accurate sensor information from a plurality of wastewaterwells in a region. For still yet another example, the aggregate systemmay be able to forecast hydrocarbon production by possessing knowledgeof water-to-oil or water-to-gas ratios in a region, as described in U.S.Patent Publication No. 2016/0063402 entitled “Oilfield WaterManagement,” which is incorporated herein by reference.

One of ordinary skill in the art will recognize that additionalembodiments and implementations are also possible without departing fromthe teachings of the present invention. This detailed description, andparticularly the specific details of the exemplary embodiments andimplementations disclosed therein, is given primarily for clarity ofunderstanding, and no unnecessary limitations are to be understoodtherefrom, for modifications will become obvious to those skilled in theart upon reading this disclosure and may be made without departing fromthe spirit or scope of the invention.

What is claimed is:
 1. A system for monitoring disposal of wastewater in a disposal well, comprising: an event monitor sensor configured to identify a wastewater disposal event; a second sensor configured to collect data about one or more characteristics of the wastewater during the wastewater disposal event; and a water analysis module operable to receive collected data from the second sensor, and further operable to determine a classification of the wastewater from the collected data.
 2. The system as recited in claim 1, wherein the event monitor sensor is a camera.
 3. The system as recited in claim 1, wherein the event monitor sensor is a current sensor.
 4. The system as recited in claim 3, wherein the current sensor monitors the power consumption of one or more pumps that are associated with the disposal well.
 5. The system as recited in claim 1, wherein the second sensor is selected from the group consisting of: a total suspended solids (TSS) sensor; a pH sensor; and a conductivity sensor.
 6. The system as recited in claim 1, wherein the second sensor comprises: a total suspended solids (TSS) sensor; a pH sensor; and a conductivity sensor.
 7. The system as recited in claim 1, wherein the classification is one of the following: produced water; flow-back water; pit water; or sediment waste.
 8. A method for monitoring disposal of wastewater in a disposal well, comprising the steps: identifying a wastewater disposal event at the disposal well; monitoring a volume of waste being disposed at the disposal well; collecting data indicative of one or more characteristics of the wastewater; determining a classification of the wastewater based on the collected data; and reporting the classification of the wastewater to an operator or another interested party.
 9. The method as recited in claim 8, wherein the step of identifying the wastewater disposal event at the disposal well includes the positioning of an event monitor sensor configured to identify the wastewater disposal event.
 10. The method as recited in claim 9, wherein the event monitor sensor is a camera.
 11. The method as recited in claim 9, wherein the event monitor sensor is a current sensor.
 12. The method as recited in claim 11, wherein the current sensor monitors the power consumption of one or more pumps that are associated with the disposal well.
 13. The method as recited in claim 9, wherein the step of collecting data indicative of one or more characteristics of the wastewater is accomplished through use of a second sensor.
 14. The method as recited in claim 13, wherein the second sensor is selected from the group consisting of: a total suspended solids (TSS) sensor; a pH sensor; and a conductivity sensor.
 15. The method as recited in claim 13, wherein the second sensor comprises: a total suspended solids (TSS) sensor; a pH sensor; and a conductivity sensor.
 16. The method as recited in claim 8, wherein the classification is one of the following: produced water; flow-back water; pit water; or sediment waste.
 17. A method for monitoring disposal of wastewater in a disposal well, comprising the steps: receiving data from an event monitor sensor in order to identify a wastewater disposal event at the disposal well; receiving data from a second sensor at the disposal well about one or more characteristics of the wastewater during the wastewater disposal event; analyzing the data from the second sensor at the disposal well to determine a classification of the wastewater; and reporting the classification of the wastewater to an operator or another interested party.
 18. The method as recited in claim 17, and further comprising a step of computing statistics for the wastewater based on the data from the second sensor during the wastewater disposal event.
 19. The method as recited in claim 17, in which the step of analyzing the data from the second sensor at the disposal well to determine the classification of the wastewater includes: establishing a water classification model based on the data collected from the second sensor during prior wastewater disposal events as compared to accurate information about the wastewater during prior wastewater disposal events acquired from an external source; and applying the water classification model to data from the second sensor during the wastewater disposal event.
 20. The method as recited in claim 19, in which the water classification model is based on a logistic regression model. 